Hi everybody
An easy issue that made me confused these days is why ESTs are used for in silico identification of miRNAs or why other types, for instance transcriptome seq data may not be suitable for?
Answers would be highly appreciated.
So first of all, what you want to have is a small RNA-seq dataset. This way you have a way to get the final product of the microRNA pathway, which are mature microRNAs. Then you want to map that dataset to a reference genome in order to see which sRNAs follow a microRNA distribution (in a transcript, microRNAs will group mainly in a certain region and not randomly across it), and also if it has a hairpin structure. Using transcriptome data is feasible BUT remember that you might not always find all possible microRNAs since they might not be expressed on your transcriptome or are being process on a high rate. So the take home message for microRNA identification is have a sRNA-seq dataset and a reference genome.
Thanks for your consideration Francisco
Actually I have different goal of what you mentioned. I want to predict miRNAs of my interest organism computationally. As I could understand from references, mostly they have used ESTs and/or gss for homology searches. Now I can not understand why ESTs are used? and how about other data like transcriptome sequencing data?
Use Infernal with the latest Rfam library. It is generic for any ncRNA
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